Strong fisheries management and governance positivelyimpact ecosystem status
Alida Bundy1, Ratana Chuenpagdee2, Jennifer L Boldt3, Maria de Fatima Borges4, Mohamed Lamine Camara5,
Marta Coll6,7,8, Ibrahima Diallo5, Clive Fox9, Elizabeth A Fulton10,11, Ayse Gazihan12, Astrid Jarre8,
Didier Jouffre13,14, Kristin M Kleisner15,a, Ben Knight16, Jason Link17, Patroba P Matiku18, Hicham Masski19,
Dimitrios K Moutopoulos20, Chiara Piroddi7, Tiit Raid21, Ignacio Sobrino22, Jorge Tam23, Djiga Thiao24,
Maria Angeles Torres22,25,b, Konstantinos Tsagarakis26, Gro I van der Meeren27 & Yunne-Jai Shin6,12
1Fisheries and Oceans Canada, Bedford Institute of Oceanography, PO Box 1006, Dartmouth, NS, Canada B2Y 4A2;2Memorial University, St. John’s, NL, Canada A1B 3X9; 3Fisheries and Oceans Canada, Pacific Biological Station, 3190
Hammond Bay Road, Nanaimo, BC, Canada V9T 6N7; 4Instituto Portugues do Mar e da Atmosfera (IPMA), Avenida de
Brasilia, Lisboa 1449-006, Portugal; 5CNSHB, 814, Rue MA 500, Corniche Sud, Boussoura Port, Conakry, BP 3738,
Republic of Guinea; 6Institut de Recherche pour le D�eveloppement, UMR MARBEC 248, CRH, Avenue Jean Monnet, CS
30171, S�ete 34203, France; 7Institut de Ci�encies del Mar (CMIMA-CSIC), P. Mar�ıtim de la Barceloneta, 37-49, 08003
Barcelona, Spain; 8Marine Research Institute and Department of Biological Sciences, University of Cape Town, Private
Bag X3, Rondebosch, Cape Town 7701, South Africa; 9Scottish Association for Marine Science, Dunstaffnage, Oban,
PA371QA, UK; 10CSIRO Oceans and Atmosphere, GPO Box 1538, Hobart, TAS 7001, Australia; 11Centre for Marine
Socioecology, University of Tasmania, Hobart, TAS 7001, Australia; 12Institute of Marine Sciences, Middle East
Technical University, Po Box 28, Erdemli, 33731, Turkey; 13Institut de Recherche pour le Developpement, UMR
MARBEC, Dakar, BP 1386, Senegal; 14Laboratoire de Biologie et d’Ecologie de Poissons en Afrique de l’Ouest (LABEP-
AO), Institut Fondamental d’Afrique Noire, Campus universitaire UCAD, Dakar, B.P. 206, Senegal; 15Sea Around Us
Project, Fisheries Centre, University of British Columbia, 2202 Main Mall, Vancouver, Canada, V6T 1Z4; 16Cawthron
Institute, 98 Halifax Street East Nelson 7010, Private Bag 2, Nelson 7042, New Zealand; 17NOAA Fisheries, 166 Water
St., Woods Hole, MA 02543, USA; 18Tanzania Fisheries Research Institute (TAFIRI), P. O. Box 9750, Dar es Salaam,
Tanzania; 19Institut National de Recherche Halieutique, Bd Sidi Abderrahmane, Casablanca 20000, Morocco;20Department of Fisheries-Aquaculture Technology, Educational Institute of Western Greece, Mesolonghi 30200,
Greece; 21Estonian Marine Institute, University of Tartu, Maealuse 14, Tallinn, EE-12618, Estonia; 22Centro
Oceanografico de Cadiz, Instituto Espanol de Oceanografıa (IEO), Puerto Pesquero, Muelle de Levante, s/n, Cadiz,
11006, Spain; 23Instituto del Mar del Peru (IMARPE), Esquina Gamarra y Gral, Valle s/n, Apartado 22, Callao, Lima,
Peru; 24Centre de Recherches Oceanographiques de Dakar-Thiaroye, Dakar, BP 2241, Senegal; 25Department of Aquatic
Resources, Institute of Coastal Research, Swedish University of Agricultural Sciences, Skolgatan 6, SE-742 42
€Oregrund, Sweden; 26Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research,
46.7 km Athens-Sounio ave., Anavyssos, Attiki 19013, Greece; 27Institute of Marine Science, IMBER and the Hjort
Centre for Marine Ecosystem Dynamics, PB 1870 Nordnes, Bergen, NO-5817, Norway; Current Address: aNOAA,
Northeast Fisheries Science Center, 166 Water Street, Woods Hole, MA 02543, USA; Current Address: bCentro de
Ciencias do Mar (CCMAR), Universidade do Algarve, Campus Gambelas, Faro, 8005-139, Portugal
AbstractFisheries have had major negative impacts on marine ecosystems, and effective
fisheries management and governance are needed to achieve sustainable fisheries,
biodiversity conservation goals and thus good ecosystem status. To date, the IndiS-
eas programme (Indicators for the Seas) has focussed on assessing the ecological
impacts of fishing at the ecosystem scale using ecological indicators. Here, we
Correspondence:
Alida Bundy, Fish-
eries and Oceans
Canada, Bedford
Institute of Oceanog-
raphy, PO Box 1006,
Dartmouth, NS,
Canada B2Y 4A2
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd. DOI: 10.1111/faf.12184 1
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License,
which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and
no modifications or adaptations are made.
F I SH and F I SHER I E S
explore fisheries ‘Management Effectiveness’ and ‘Governance Quality’ and relate
this to ecosystem health and status. We developed a dedicated expert survey,
focused at the ecosystem level, with a series of questions addressing aspects of man-
agement and governance, from an ecosystem-based perspective, using objective
and evidence-based criteria. The survey was completed by ecosystem experts (man-
agers and scientists) and results analysed using ranking and multivariate methods.
Results were further examined for selected ecosystems, using expert knowledge, to
explore the overall findings in greater depth. Higher scores for ‘Management Effec-
tiveness’ and ‘Governance Quality’ were significantly and positively related to
ecosystems with better ecological status. Key factors that point to success in deliv-
ering fisheries and conservation objectives were as follows: the use of reference
points for management, frequent review of stock assessments, whether Illegal,
Unreported and Unregulated (IUU) catches were being accounted for and addressed,
and the inclusion of stakeholders. Additionally, we found that the implementation
of a long-term management plan, including economic and social dimensions of
fisheries in exploited ecosystems, was a key factor in successful, sustainable fish-
eries management. Our results support the thesis that good ecosystem-based man-
agement and governance, sustainable fisheries and healthy ecosystems go together.
Keywords Ecological indicator, ecosystem-based fisheries management (EBFM),
expert evaluation, fisheries governance quality, fisheries management effectiveness,
socioeconomic indicators
Tel.: +902 426 8353
Fax: +902 426 1506
E-mail: alida.bundy@
dfo-mpo.gc.ca
Reproduced with the
permission of the
Minister of Fisheries
and Oceans Canada.
Received 13 Apr
2016
Accepted 11 Aug
2016
Introduction 2
Methods 5
Survey questionnaire 5
Data analysis 6
Survey Results 6
Multivariate Analysis 6
Relationship to additional ecosystem characteristics 9
Results 10
Management Effectiveness and Governance Quality Survey results 10
Background Experts and Ecosystem data 10
Survey Results 12
Multivariate Analysis 14
Relationship to other ecosystem characteristics – BEST Analysis 16
Discussion 18
Relationship to other ecosystem characteristics 20
A more nuanced view of the results 21
Conclusions 24
Acknowledgements 24
References 24
Supporting Information 28
Introduction
The oceans provide critical ecosystem services
(Alcamo et al. 2003; MEA 2005; Liquete et al.
2013), among which are food provisioning and food
security, traditionally accessed by fishing at multiple
scales, from local subsistence fishing to small-scale
artisanal fisheries, and to larger scale industrial
2 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
operations. Harvesting marine living resources at
all scales has the potential to alter marine ecosystem
structure and functioning, and thus, impact the ser-
vices that seas and oceans provide. Therefore, how
we manage and govern human activities in our
oceans has a direct impact on their overall health
and ability to provide the benefits that we derive
from them now and into the future.
This link between management, governance
and ecosystem health is reflected by the evolving
nature of fisheries management and the wide-
spread recognition of the need for an ecosystem-
based approach to fisheries (FAO 2003). Over the
last two decades, in an attempt to highlight and
service this need, there has been substantial effort
to evaluate the ecological status of marine ecosys-
tems, through initiatives such as the Scientific
Committee on Ocean Research/Intergovernmental
Oceanographic Commission (SCOR/IOC) Working
Group (WG) on Quantitative Ecosystem Indicators
for Fisheries Management (Cury and Christensen
2005), International Council for the Exploration of
the Sea (ICES) Working groups such as the ICES
WG on Ecosystem Effects of Fishing Activities
(WGECO, ICES 2015a), the ICES WG on Biodiver-
sity Science (WGBIODIV, ICES 2015b), and the
IndiSeas (Indicators for the Seas) programme (Shin
et al. 2010, 2012; Bundy et al. 2012). However,
evaluation of the human dimensions of fisheries
has received relatively less attention although they
are explicitly recognized as a key element of
ecosystem-based fisheries management, EBFM (Les-
lie and McLeod 2007; De Young et al. 2008). Eco-
nomic outcomes have garnered some regional to
global research efforts (e.g. Browman et al. 2005;
Sumaila et al. 2006, 2011) while social well-being
has been considered in some locations (e.g.
Coulthard et al. 2011; Coulthard 2012). With
respect to management and governance, some
studies have been conducted to evaluate the effec-
tiveness of governance overall (Pitcher et al. 2006,
2009a; Mora et al. 2009; Coll et al. 2013), but
there is a lack of specific studies that link gover-
nance to ecosystem status.
Understanding the status and effectiveness of
management and governance can provide impor-
tant insights and linkages to the ecological status of
marine ecosystems. In a global study, Pitcher et al.
(2006, 2009a) assessed the extent to which 53 fish-
ing nations, accounting for 96% of the global mar-
ine catch in 1999, complied with the Food and
Agriculture Organization of the United Nations
(FAO) Code of Conduct for Responsible Fisheries
(CCRF, FAO 1995). Their evaluation method, com-
prised of 44 questions, was based on Article 7 of the
CCRF and the rapid appraisal technique, Rapfish
(Pitcher, 1999, Pitcher et al. 2013). They devel-
oped a two-stage process whereby the authors ini-
tially scored the 53 nations based on available
literature, including grey reports. In the second
stage, their assessment was externally validated by
independent experts, although this only included
33 nations (Pitcher et al. 2006). They concluded
that globally, compliance was poor: no country
reached their ‘good’ status and 28 countries failed
‘unequivocally’; the three best performing countries
were Norway, USA and Canada. In a further study,
Pitcher et al. (2009b) used the previous 2006
results to score how well EBFM was being imple-
mented worldwide, again concluding that no coun-
try rated as ‘good’, and over half received failing
grades. Coll et al. (2013) took these results further
by exploring the relationship between compliance
with the CCRF and different measures of ecosystem
health, and they concluded that greater compliance
does result in greater ecosystem sustainability. They
based their approach on the ‘Psust’ indicator, that
is the probability of the ecosystem to be sustainably
fished (Libralato et al. 2008). Their results linked
compliance by country to ecosystem sustainability
of fisheries, highlighting that countries with a
higher level of compliance with the FAO Code of
Conduct in 2008 experienced an increase in fish-
eries sustainability from the 1990s to 2000s.
In another global study, Mora et al. (2009) eval-
uated the management effectiveness of marine
fisheries using an expert elicitation approach
through an online survey. They developed their
survey questions based on six factors: scientific
robustness, transparency, enforcement compliance,
fishing capacity, subsidies and foreign fishing.
They contacted over 13 000 fisheries experts, with
a 9% success rate (1188 responses) covering 236
EEZs, although only 209 were used in their final
statistical analyses (see Mora et al. 2009 for fur-
ther details). Like Pitcher et al. (2006), they con-
cluded that fisheries management was poor
overall: only 7% of nations surveyed had manage-
ment policies that were based on rigorous scientific
assessment, very few had participatory and trans-
parent processes for converting scientific recom-
mendations into policy (1.4%), and less than 1%
had sufficient mechanisms to ensure compliance
with regulations. They then assessed the
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 3
Good fisheries management and governance A Bundy et al.
relationship between their results with the sustain-
ability of reported fisheries catches (Libralato et al.
2008). They concluded that ‘the conversion of sci-
entific advice into policy, through a participatory
and transparent process, is at the core of achiev-
ing fisheries sustainability, regardless of other
attributes of the fisheries’ (Mora et al. 2009).
Cullis-Suzuki and Pauly (2010) explored how
well regional fisheries management organizations
(RFMOs) comply with a code of best practices for
RFMOs by analysing available information from
reports. They concluded that, on paper, and based
on empirical evidence related to stock status, the
RFMOs scored poorly on average. They also con-
cluded that there is a gap between what was
intended on paper and material outcomes. Simi-
larly, Skern-Mauritzen et al. (2016) evaluated the
degree to which ecosystem processes were
included in the scientific information provided for
management decisions and advice regarding catch
levels. They discovered that ecosystem considera-
tions were included less than 2% of the time. As
such, the implementation of the EBFM is deemed
lagging and concerns for management effective-
ness remain.
The FAO has adopted the general survey
approach proposed by Pitcher et al. (2006), and
since 2013, it has surveyed member States, Regio-
nal Fisheries Bodies and International Non-Govern-
mental Organizations using a web-based platform,
‘Progress in the Implementation of the Code of
Conduct for Responsible Fisheries and Related
Instruments’ (http://www.fao.org/fishery/topic/
166326/en). Results are published in annual
reports, at an aggregated level (e.g. FAO 2014a,b).
These studies underscore the importance of
looking beyond the ecological status of marine
ecosystems to include management and gover-
nance, which are key drivers of fishery systems.
However, the studies cited above (Pitcher et al.
2006, 2009a,b; Mora et al. 2009; Cullis-Suzuki
and Pauly 2010; Coll et al. 2013) were all con-
ducted at national or larger spatial scales, and
information was collected and analysed remotely
by the authors of the studies. Although National
Fisheries policies do apply at these scales, in prac-
tice fisheries governance and management gener-
ally occur at smaller, more regional scales, such
as at the fishery or stock scale (e.g. ICES Divisions,
North Atlantic Fisheries Organization [NAFO] Divi-
sions, coastal fisheries such as ‘lobster fishing
areas’). More recently, with growing interest in
ecosystem-based fisheries management, there has
been increased recognition of the need for man-
agement at the ecosystem level, a scale that often
does not match jurisdictional boundaries, which
may be broader than the scale of individual stocks
or fisheries, but may better account for ecological
processes (Link 2010). Here, we define ‘ecosystem
scale’ as the spatial scale that encompasses the
majority of the species and fisheries interactions
within a region (Garcia and Charles 2008). Obvi-
ously due to differences between regions, the size
and demarcation of an ecosystem will be context
dependent. However, to the extent possible, it is
important to try to match ecosystem, jurisdictional
and management boundaries (Garcia and Charles
2008), and this usually occurs at spatial scales
smaller than large marine ecosystems (Fogarty
and Rose 2013). Co-design and co-creation of
knowledge is increasingly recognized as a robust
and meaningful approach to Science (e.g. Mauser
et al. 2013). Here, we propose to explore the rela-
tionship between management, governance and
ecosystem status at the ecosystem scale, including
expert knowledge in the survey design, survey
completion and interpretation of the survey data.
The IndiSeas programme (www.indiseas.org)
has conducted comparative analyses across many
of the world’s marine ecosystems to quantify the
impact of fishing using a suite of ecological indica-
tors that are robust over diverse and contrasting
conditions and a combination of data driven and
ecosystem modelling approaches (e.g. Shin et al.
2010, 2012; Bundy et al. 2012; Shannon et al.
2014; Fu et al. 2015; Coll et al. 2016). Although
the original focus of the IndiSeas programme was
on the ecological status of exploited ecosystems, it
has since extended its scope to include the human
dimensions of fisheries in marine ecosystems, rec-
ognizing that management and governance effec-
tiveness is likely to be linked to the status of the
exploited ecosystem and that the importance and
contribution of fisheries to society and community
well-being should be evaluated.
A key emphasis of the IndiSeas programme has
been on comparative analyses at the ecosystem
scale for EBFM, matching the scale of the analysis
to the scale of the system, and critically, the use of
local survey data, and local expert knowledge to
provide information and to interpret results: IndiS-
eas members include experts from all IndiSeas
ecosystems. The IndiSeas approach, which tries to
extract patterns from complex local realities, is
4 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
hence fully complementary to existing global
meta-data analyses. For each ecosystem included
in the IndiSeas programme, an ecosystem expert
defines the scale of the ecosystem, which currently
range in size from 1000 to 3 700 000 km2 (for
further details see www.indiseas.org). In this
study, we assess management and governance at
the ecosystem scale across a broad suite of ecosys-
tems using expert knowledge, explore how man-
agement and governance relates to the ecological
status of exploited ecosystems, and identify what
factors are important for success. We do this by
developing a parsimonious expert survey question-
naire, using evidence-based criteria, to evaluate
the ‘Management Effectiveness’ and ‘Governance
Quality’ of ecosystems included in the IndiSeas
programme at the ecosystem level. Further, we
explore how the results of this survey relate to
other factors and indicators of ecosystem and stock
status, and test the hypothesis that ecosystems
with better management and governance are more
sustainable, with higher scores for ecosystem and
stock status. We use the results of this analysis to
identify potential ways to improve fisheries man-
agement and governance and the sustainability of
exploited ecosystems.
Methods
Survey questionnaire
An expert elicitation approach was used to assess
fisheries management effectiveness and gover-
nance quality in exploited ecosystems included in
the IndiSeas programme. Expert elicitation has
been widely used to gather information in the
social and natural sciences (e.g. Lenton et al.
2008; Choy et al. 2009; Runge et al. 2011). An
expert is defined as someone who is a knowledge
integrator (representing broad expertise), has pro-
fessional integrity (representing consensus, rather
than just their own opinion) and has skills in ana-
lytical judgment, with particular knowledge of a
given topic or area (Burgman et al. 2011). For this
analysis, we targeted fisheries managers and scien-
tists who are closely involved with providing fish-
eries management advice in each of the
ecosystems analysed. Specific guidelines were
developed to define who was eligible to complete
the survey, based on the definition of an expert
given above. The surveys were initially sent to the
ecosystem representatives on the IndiSeas
programme, who were then asked to use their
expert judgement to select additional relevant
experts to complete the survey template. Informa-
tion about the experts completing the survey was
collected to assess their expertise (Table 1). The
reference time period for the survey is over recent
years (e.g. 2005–2012), to be coherent with the
ecological indicators.
Generally speaking, we consider routine activi-
ties and those of a technical nature, with well-spe-
cified targets and goals, as part of management.
Governance, on the other hand, is a broader con-
cept that emphasizes the importance of processes,
the roles of institutions, the legal mandate and
authority to govern, and the involvement of actors
and stakeholders. The aims of governance also go
beyond achieving certain objectives to providing
mechanisms that enable relevant sectors to articu-
late their interests, establishing institutions that
allow them to exercise their rights and meet their
obligations, and formulating principles and values
that serve as a basis for mediating differences and
making decisions affecting society (Kooiman et al.
2005; Chuenpagdee 2011).
We used the questions from Pitcher et al.
(2006) as a starting point to develop a
Table 1 Information required about ecosystem and
fisheries experts completing the Management
Effectiveness and Governance Quality Survey.
Expert Information Fishery/Sector Information
Name Name of countryAffiliation Name of ecosystemJob title and description Number of different
fisheries/fisheriessectors in the ecosystem
Specialization Name of fishery orfishery sector
Highest degree Year of currentmanagement plan
Number of years in this job Number of differentfisheries includedin this sector
Number of years’ experiencein Fisheries
Total number of targetedspecies in this sector
Number of years’ experiencein related field (e.g. sociologicalresearch/fisheries management)
Annual total catch for thisfishery or fishery sectorfrom most recent year(indicate year)
International experience(Yes/No, Where?)
Member of IndiSeas (Yes/No)
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 5
Good fisheries management and governance A Bundy et al.
parsimonious, short survey of management effec-
tiveness and governance quality of exploited
ecosystems in the IndiSeas programme. To this
end, by means of an iterative process, we selected
a subset of questions using the following criteria:
the question should be clearly stated, objective,
supportable by evidence and address management
effectiveness or governance quality. Of the 44
questions used by Pitcher et al. (2006), 13 were
initially selected for this study. These were then
tested using a subset of IndiSeas ecosystems and
revised based on the feedback of the local experts
completing the questionnaire (i.e. the survey was
co-designed by IndiSeas and a subset of local
ecosystem experts). The survey was then com-
pleted for 23 IndiSeas ecosystems and the results
presented to the larger IndiSeas membership dur-
ing the annual 2011 and 2012 IndiSeas meetings.
The survey was revised, to further reduce subjec-
tivity and ambiguity in the questions, based on
feedback from the participants of the annual meet-
ings. The final survey consisted of 11 questions
(Table 2), encompassing 18 of the 44 questions in
Pitcher et al. (2006), and all surveys were com-
pleted by 2013.
Of the 11 questions, six were related to manage-
ment effectiveness and five to governance quality
(Table 2). Management effectiveness questions
were focussed on specific details of fish stock and
ecosystem management, such as reference points
and whether ecosystem impacts are addressed.
The governance quality questions were focussed
on whether the social and economic dimensions of
fisheries were addressed in their longer term gov-
ernance plans and whether there is transparency
in decision making. Some questions were focussed
at the species/stock level, and others reflect an
ecosystem perspective. By combining these two
aspects, we have developed a parsimonious survey
that details the essential elements required for
EBFM.
A glossary of terms (see Table S1) was provided
to ensure that all questions were fully understood,
and experts were asked to provide references as
evidence to support their responses. The 11 ques-
tions were framed as multiple choice questions,
with five or six possible responses scored on a 5-
point scale, where 5 was the highest score. In the
few cases where there was a sixth option, it was
considered equivalent to option 5 for comparative
purposes (see Table S1 for a full version of the
Survey Questionnaire and guidelines).
To capture the majority of fisheries that con-
tribute to the landings from the ecosystem, experts
were asked to complete the survey for all the fish-
eries that account for a minimum of 80% of the
total landings by volume. If separate management
plans existed for the different fisheries, experts
were asked to complete the questions for each
main management plan. Groupings could there-
fore be by target species, sector or management
type or by gear type – for example small-scale
longline, small-scale trap fishery and mid-water
trawl fishery. A single score for each question was
calculated as the average of all fisheries/sectors,
weighted by their total landings.
In many cases, several experts representing the
different fisheries/sectors in the ecosystem com-
pleted the survey. In cases where more than one
expert independently completed the survey for the
same fishery or sector and the scores were mark-
edly different, the experts were contacted again,
and a consensus approach was used to arrive at a
single response.
Data analysis
Survey results
The Management Effectiveness and Governance
Quality Survey results (the Survey results hence-
forth) were first explored to evaluate and summa-
rize the information provided by the survey
respondents about their expertise and experience
to provide contextual information to help evaluate
the quantitative analyses described below.
The responses to the 11 questions were then
explored to elucidate the major patterns in the
data and to summarize and rank results. Finally,
the rank order of the IndiSeas ecosystems, using
the average of the 11 questions, was compared
with the rank order based on compliance with the
CCRF (Pitcher et al. 2009a). In cases where an
ecosystem straddled more than one national juris-
diction, the CCRF scores for each country border-
ing the ecosystem were averaged, using their total
average annual landings from the ecosystem
(2000–2010) as a weighting factor, to estimate an
average ecosystem compliance score – see
Table S2 for further details.
Multivariate analysis
A range of multivariate methods was used to explore
the results of the Survey using the statistical pack-
age PRIMER (6.1.2, PRIMER-E Ltd, Plymouth, UK).
6 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Table 2 Management Effectiveness and Quality of Governance Survey questions. Right-hand column indicated the
question numbers from Pitcher et al. (2006) to which the survey questions relate.
Assess the Effectiveness of Management Pitcher et al. (2006)
1. How frequently are stock assessments* carried out in your fisheryor fishery sector?
i. No stock assessments are being carried outii. Infrequent for less than 50% of commercial stocksiii. Infrequent for more than 50% of commercial stocksiv. Every 1–5 years for less than 50% of commercial stocksv. Every 1–5 years for more than 50% of commercial stocks
na
2. Are limit reference points*, thresholds*, or other targets*, set and usedfor the management of commercial stocks and/or species at risk?
i. No reference points existii. Reference points exist for less than 50% of stocks/species but are not implementediii. Reference points exist for less than 50% of stocks/species and are implementediv. Reference points exist for more than 50% of stocks/species and are implementedv. Reference points exist for more than 50% of stocks/species are implemented andregularly reviewed
1,19,20
3. Are depleted stocks* or species* being successfully rebuilt?
i. Noii. The intention to rebuild is in the management plan, but there is no mechanism inplace to enable rebuilding
iii. Rebuilding effort occurs, but it is not effectiveiv. Effective rebuilding* of less than 50% of depleted stocks/speciesv. Effective rebuilding of more than 50% depleted stocks/speciesvi. No depleted stocks or species caught in this fishery or fishery sector
5, 32
4. Are management measures* being reviewed frequently enough tomaximize the prospect that the management intentions* are met?
i. No reviewii. Infrequent review and management intentions not being metiii. Infrequent review, but some management intentions being metiv. Frequent enough review to maximize the prospect that most managementintentions are met
v. Frequently enough review to maximize the prospect that all managementintentions are met
23
5. Are ecosystem impacts* of fishing assessed, and are they being addressed?
i. No ecosystem impact assessmentii. Some ecosystem impact assessment, but no impacts are being addressediii. Some ecosystem impact assessment, and some impacts are being addressediv. Comprehensive ecosystem impact assessment, and some impacts are being addressedv. Comprehensive ecosystem impact assessment, and all impacts are being addressed
8,25
6. Is Illegal*, Underreported* and Unregulated* (IUU) fishing beingaddressed by management?
i. Noii. The intention to address IUU is in the management plan, but there is no mechanism in
place to enable actioniii. Some mechanisms to address IUU are in the management plan, but they are not effectiveiv. Mechanisms to address IUU are in the management plan, and they are partly effectivev. Mechanisms to address IUU are in the management plan, and they are effectivevi. Not applicable (i.e. there is no IUU)
42,43
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 7
Good fisheries management and governance A Bundy et al.
Prior to analysis, the Survey data were standardized
using the ‘normalize’ routine in PRIMER. Survey
results were first examined using Draftsman plots
to assess skewness in the data and Spearman rank-
order correlations were used to test for correlations
between the 11 questions: the maximum Spearman
rank correlation was 0.82, with an average of
0.46, so all questions were used in the analysis.
The Survey data were then explored using a
standard principle components analysis (PCA) and
a hierarchical agglomerative cluster analysis based
on Euclidean distance. The group average option
was used to link clusters, which is based on the
mean similarity between all samples in two
groups. Significance of the cluster results was
tested using the ‘SIMPROF’ permutation test,
which examines whether the similarities observed
in the data are smaller and/or larger than those
expected by chance (Clarke et al. 2008). We used
1000 permutations and an alpha of 5%.
Table 2 Continued.
Assess the Effectiveness of Management Pitcher et al. (2006)
Assess Quality of Governance Pitcher et al. (2006)7. Is this fishery managed so as to minimize conflict* with other fishery sectors?
i. Conflict is not acknowledgedii. Conflict is acknowledged but not addressediii. Conflict is addressed, but has little effectiv. Conflict is addressed, but only partly effectivev. Conflict management is very effectivevi. Not applicable
33
8. Does the fishery or fishery sector management plan have long-term objectives*?
i. no long-term objectives in management planii. yes, but no specific ecological, social or economic long-term objectivesiii. yes, but only with one of the following long-term objectives: ecological, economic or socialiv. yes, but only with two of the following long-term objectives: ecological, economic or socialv. yes, with ecological, economic and social long-term objectives
12
9. Are the social impacts of the fisheries management plan considered and formallyevaluated in management decisions?
i. Social impacts not consideredii. Social impacts considered, but not formally evaluated*iii. Social impacts formally evaluated, but with no change to management decisionsiv. Social impacts formally evaluated, with some required changes reflected in management decisionsv. Social impacts formally evaluated, with all required changes reflected in management decisions
34,35,37
10. Are economic impacts of the fisheries management plan considered and evaluatedin management decisions?
i. Economic impacts not consideredii. Economic impacts considered, but not formally evaluated*iii. Economic impacts formally evaluated, but with no change to management decisionsiv. Economic impacts formally evaluated, with some required changes reflected in management decisionsv. Economic impacts formally evaluated, with all required changes reflected in management decisions
16,36
11. Is the participation of the harvesting sector a requirement in fisheries management?
i. No requirementii. Required but limited to information provision to harvesting sectoriii. Required and includes some two-way information exchangeiv. Required and involves full exchange of informationv. Required, involves full exchange of information and input to management decisions
13,14
*Asterisks denote terms that are explained in the glossary - see Table S1 for further details.
8 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Relationship to additional ecosystem characteristics
In order to place the Survey results in a broader
context, and to gain understanding of the result-
ing patterns and groupings, we explored their rela-
tionship with national social, economic and
governing conditions and with ecosystem status.
There is a wealth of potential indicators to mea-
sure these conditions, and we initially selected
thirteen commonly used and accepted indicators of
national social, economic and governing condi-
tions, available at the global scale from a range of
sources, and three indicators of ecosystem status
and ecosystem size. Where possible the data were
extracted for 2005–2012 (see Table S3 for further
details) and standardized using the ‘normalize’
routine in PRIMER. Spearman rank-order correla-
tions were used to evaluate whether there were
any correlations between these additional ecosys-
tem characteristics, using a coefficient of 0.85 as a
threshold. Of the 17 additional ecosystem charac-
teristics (Table S3), most were highly correlated
with at least one other indicator (Table S4).
Redundant ecosystem characteristics were
removed, reducing the number of additional
ecosystem characteristics to eight (Table 3): two
socioeconomic indicators – the Human Develop-
ment Index (HDI, http://hdr.undp.org/en, accessed
February 2016) and Research and Development
(R and D, http://hdr.undp.org/en, accessed Febru-
ary 2016), two broad governance indicators – Bad
Fisheries Subsidies (B-SUBS, Khan et al. 2006) and
Political Stability and Absence of Violence/Terror-
ism (PS, Kaufmann et al. 2011), three indicators
of ecosystem status – Sustainable Stocks (SS, Shin
et al. 2010; Coll et al. 2016), Non-Declining
Exploited Species (NDES, Kleisner et al. 2015), and
an IndiSeas aggregate indicator of ecosystem sta-
tus (ES, Bundy et al. 2012), and Ecosystem Size
(Size). See Table S3 for further details.
The PRIMER BEST routine was used to investi-
gate whether there was a relationship between the
results of the multivariate analysis of the Survey
data and the nine ecosystem characteristics. It
selects the ecosystem characteristics that globally
best explain the variability in the Survey data.
Specifically, it calculates the correlation coefficients
between the similarity matrices of the Survey data
and the ecosystem characteristics and identifies
the combination of ecosystem characteristics that
maximize the correlation between the two similar-
ity matrices. Some of the additional ecosystem
characteristics were transformed; all were stan-
dardized prior to analyses. The statistical signifi-
cance of the results of the BEST analyses was
assessed using a permutation test (Clarke et al.
2008).
The social, economic, governing and size indica-
tors were available for all ecosystems, but the
additional IndiSeas ecological indicators, SS, NDES
and ES, were only available for a subset of the
total of the ecosystems included in the Survey. To
fully explore all the ecological indicators, and
maximize the number of ecosystems in the analy-
sis, four separate BEST analyses were explored:
1. BEST 1: All ecosystems, excluding, SS, NDES
and ES (n = 27)
2. BEST 2: Only ecosystems with SS data, exclud-
ing NDES and ES indicators (n = 25)
3. BEST 3: Only ecosystems with SS and NDES
data excluding ES indicator (n = 18)
Table 3 Social, economic, governance and ecological indicators used in the BEST analyses.
Social, Economic and Ecological Indicators SourceNumber ofecosystems
1. Ecosystem Size (Size) IndiSeas 2 272. Human Development Index (HDI) International Human Development Indicators – UNDP
http://hdr.undp.org/en (accessed Feb 2016)27
3. Research and Development (% of GDP):average 2006–2012 (R&D)
4. Bad Fisheries Subsidies – % GDP (Bad-SUBS) Sumaila and Pauly (2006) 275. Political Stability and Absence of Violence/Terrorism (PS) The Worldwide Governance Indicators
www.govindicators.org (accessed Feb 2016)27
6. Sustainable Stocks – Proportion of moderately andunderexploited species (SS)
IndiSeas, Shin et al. (2010); Coll et al. (2016) 25
7. NDES: Non-Declining Exploited Species IndiSeas, Kleisner et al. (2015) 188. ES: Ecosystem Status (�1, 0, +1) IndiSeas, Bundy et al. (2012) 13
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 9
Good fisheries management and governance A Bundy et al.
4. BEST 4: Only ecosystems with all additional
ecological indicators (n = 11)
These four analyses differed in the number of
ecosystems and ecological indicators included. As
a statistical check to ensure that any differences in
results between the four BEST analysis were due
to the combination of indicators and not the differ-
ence in number of ecosystems included in the
analysis, BEST 1, 2, 3 and 4 were rerun as BEST
1a, 2a and 3a without the ecological indicators
SS, NDES and ES.
Results
Management effectiveness and governance quality
survey results
Background experts and ecosystem data
Survey templates were completed by 61 experts
from 27 IndiSeas ecosystems (Fig. 1, Table 4). On
average, there were 2.3 experts per ecosystem sur-
vey template, although in 15 cases only one
expert completed the survey (Table 5). In the 12
cases where more than one expert completed the
survey, most responses were for different fishery
sectors. In cases where more than one expert pro-
vided information for the same sector, a consensus
approach was used in one case, and an average
taken in the other cases as the differences were
minor. Each expert had an average of 18 years of
experience in fisheries, and 13 years in sociologi-
cal research and/or fisheries management. Over
half (40) of the experts were from government
institutions, 20 from academia and 1 from an
NGO. All experts were university educated, with
most having PhDs or MScs, and most were senior
researchers or above (Table 5b).
The 27 systems ranged in size from 1000 to
3 700 000 km2, with an average size of
346 000 km2 and a median size of 89 000 km2
(Tables 4 and 5c). Four ecosystems were defined
at the same scale as the country’s EEZ (Portugal,
Guinea, northern Humboldt and Senegal), and the
rest were either ecosystems within the EEZ includ-
ing the two largest ecosystems, south-east Aus-
tralia and the West Coast USA, or were
ecosystems that straddled national boundaries.
The respondents were asked to define the number
of different fisheries or fisheries sectors in the
ecosystem, which varied from one to fifteen, with
a median value of four. The survey was subse-
quently completed for each of these sectors. In
practice, experts were only required to complete
the survey for sectors that contributed to a mini-
mum of 80% of the landings by volume, so the
maximum number of sectors in any ecosystem for
Figure 1 Map showing the location and size of the 27 IndiSeas ecosystems included in this analysis. 1 = Barents Sea,
2 = Bay of Ambaro, 3 = Biscay Bay, 4 = Black Sea (Turkish Waters), 5 = Central Baltic Sea, 6 = Chatham Rise,
7 = Eastern English Channel, 8 = Eastern Scotian Shelf, 9 = Guinean Shelf, 10 = Gulf of Cadiz, 11 = Gulf of Gabes,
12 = Irish Sea, 13 = North Aegean Sea, 14 = North Ionian Sea, 15 = North-central Adriatic Sea, 16 = North-east
USA, 17 = Northern Humboldt Current, 18 = Portugal, 19 = Prince Edward Islands, 20 = Rufiji-Mafia Channel,
21 = Sahara Coastal Morocco, 22 = Senegalese Shelf, 23 = South-east Australian Shelf, 24 = Southern Benguela
Current, 25 = Southern Catalan Sea, 26 = West Coast USA, 27 = West Coast Vancouver Island. Map prepared by
Herve Demarcq, IRD, France.
10 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Table 4 List of 27 exploited marine ecosystems included in the IndiSeas Survey, additional ecosystem characteristics
and indication of the availability of data to calculate the indicators in each ecosystem.
Ecosystems Label Ocean/SeaEcosystemtype
SIZE(km2* 1000) HDI Subs WGI SS NDES IndiSeas
1 Barents Sea BAREN NE Atlantic High latitude 677 Y Y Y Y Y Y2 Bay of Ambaro,
MadagascarMADAG SW Indian Tropical 5 Y Y Y na na na
3 Biscay Bay BISCA NE Atlantic Temperate 202 Y Y Y Y Y na4 Black Sea
(Turkish Waters)BLCK Black Sea Temperate 18.4 Y Y Y Y Y na
5 Central Baltic Sea BALTI NE Atlantic Temperate 248 Y Y Y na Y Y6 Chatham Rise CHATH SW Pacific Temperate 167 Y1 Y Y Y na na7 Eastern
English ChannelCHANN NE Atlantic Temperate 26 Y Y Y Y Y na
8 Eastern ScotianShelf
ESS NW Atlantic Temperate 89 Y Y Y Y Y Y
9 Guinean Shelf GUINE E CentralAtlantic
Tropical 47 Y2 Y Y Y Y Y
10 Gulf of Cadiz CADIZ NW Atlantic Temperate 8.9 Y Y Y Y Y na11 Gulf of Gabes GABES C Mediterranean
SeaTemperate 36 Y3 Y Y Y na na
12 Irish Sea IRISH NE Atlantic Temperate 58 Y Y Y Y Y Y13 North Aegean Sea AEGEA E Mediterranean
SeaTemperate 8 Y Y Y Y Y na
14 North Ionian Sea IONIA C MediterraneanSea
Temperate 1 Y Y Y Y Y na
15 North-centralAdriatic Sea
ADRIA C MediterraneanSea
Temperate 55.5 Y Y Y Y Y Y
16 North-east USA NEUS NW Atlantic Temperate 297 Y Y Y Y Y Y17 Northern
Humboldt CurrentNHUMB SE Pacific Upwelling 149 Y Y4 Y Y Y Y
18 Portugal PORTU NE Atlantic Upwelling 24 Y Y Y Y Y Y19 Prince Edward Islands PE_IS S Indian High latitude 431 Y Y Y Y na na20 Rufiji-Mafia Channel,
TanzaniaTANZA SW Indian Tropical 1.2 Y Y Y Y na na
21 Sahara CoastalMorocco
SAHAR E Central Atlantic Upwelling 57 Y Y Y Y na na
22 Senegalese Shelf SENEG E CentralAtlantic Ocean
Upwelling 159 Y Y Y Y na Y
23 South-EastAustralian Shelf
AUST SW Pacific Ocean Temperate 3700 Y Y Y Y na na
24 SouthernBenguela Current
SBENG SE AtlanticOcean
Upwelling 244 Y5 Y Y Y Y Y
25 Southern Catalan Sea CATAL NW MediterraneanSea
Temperate 5 Y Y Y Y Y Y
26 West Coast USA NWUS NE PacificOcean
Upwelling 2000 Y Y Y Y Y na
27 West CoastVancouverIsland
WCVI NE PacificOcean
Upwelling 4.7 Y Y Y Y Y Y
1No IHDI or HDI-loss data for New Zealand, so values from Australia were used, pro-rated by the ratio of their HDI values (0.98).2No Research and Development data were available so the average for Africa was used.3No IHDI or HDI-loss data for Tunisia for 2012, so values from 2014 were used.4No UNDP Research and Development data were available, so the value from Chile was used, pro-rated by the ratio of their HDIvalues (0.9).5No IHDI or HDI-loss data for New Zealand for 2012, so values for 2014 were used.
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 11
Good fisheries management and governance A Bundy et al.
which the survey was actually completed was
eight (Table 5c).
Survey results
All questions received a wide range of responses
(Fig. 2 and Table S5), most spanning the range of
options. Of the six questions focussed on Manage-
ment Effectiveness, the highest scores were
obtained for Q1, which asked ‘How frequently are
stock assessments carried out in your fishery or
fishery sector?’, and the lowest scores were for Q2,
which asked ‘Are limit reference points, thresh-
olds, or other targets, set and used for the man-
agement of commercial stocks and/or species at
risk?’ and Q5, which asked ‘Are ecosystem impacts
of fishing assessed, and are they being addressed?’.
Table 5 (a) Summary of metadata from Management Effectiveness and Quality of Governance Survey: responses from
Experts Part 1: average of numerical responses. (b) Summary of responses from Experts Part 2: count of categorical
responses. (c) Summary of information about the ecosystems.
Total numberof experts
Number of yearsin this job
Number ofyears of experiencein Fisheries
Number of years’ experience in related field(e.g. sociological research/fisheries management)
(a)Average 2.3 14.2 18.0 13.5Mode 1 6.0 19.0 0.0Min 1 3.0 3.0 0.0Max 8 35.0 35.0 35.0# >1 12 26 25 20No response 1 2 2SUM 61
Option
Job title anddescription: 1 = Government;2 = Academic; 3 = NGO;4 = other;
Seniority1: 1 = head scientist;2 = senior scientist/professor;3 = lead researcher/manager;4 = researcher; 5 = postdoc/student
Highest degree1:
1 = PhD;2 = MSc,3 = BSc,4 = other:
Internationalexperience1
(Yes/No, Where?)1 = widely2 = ICES/STECF/PICES;3 = Y, some inregion; 4 = N0
(b)1 40 3 18 62 20 8 7 63 1 8 0 114 0 8 1 45 na 0 na naNo response 0 0 1 0
Number offisheries/fisheriessectors
Number offisheries/fisheriessectorsdefined
Year of currentmanagement plan
Number ofdifferentfisheries
Total numberof targetedspecies
Annual total catchfor most recent year(indicate year)
Size(km2*1000)
(c)Min 1 1 1994 1 1 84 1Max 15 8 2013 21 60 1 500 0000 3700Average 5 4 2009 7 23 1 012 547 346Median 4 4 2011 6 20 80 822 89
1
For Surveys completed by more than one expert an average was used. Therefore, these columns sum to the total number ofecosystems, 27.
12 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Questions 3, 4 and 6 had similar average scores of
around 3.4. Of the five Governance Quality ques-
tions, Q7 (Is this fishery managed so as to mini-
mize conflict with other fishery sectors?) achieved
the highest score and Q9 (Are the social impacts
of the fisheries management plan considered and
formally evaluated in management decisions?) and
Q10 (Are the economic impacts of the fisheries
management plan considered and formally evalu-
ated in management decisions?) received the low-
est scores (Fig. 2).
Overall, the Governance Quality questions
received lower scores (l = 2.88, r = 0.88) than
the Management Effectiveness questions (l = 3.37,
r = 1.0), and Question 1 had the highest score
overall. Further, the greatest variation of responses
was for Governance Quality Q8 (Does the fishery
or fishery sector management plan have long-term
objectives?) (l = 2.88, r=1.49), and the narrowest
range of responses was for Q5 (l = 2.59,
r = 0.64).
No ecosystem received an average score of 5
over the 11 questions, and only 6 scored 4 or
over, Fig. 3. When rank ordered, the three ecosys-
tems with the highest scores across all questions
were the south-east Australian Shelf, the West
Coast USA and the Barents Sea, and the three
lowest were the southern Catalan Sea, the Gui-
nean Shelf and north Ionian Sea (Fig. 3). When
the Survey results were ranked separately as Man-
agement Effectiveness and Governance Quality,
the ecosystems with the lowest three scores did
not change, but the rank order of other ecosys-
tems did, including the ecosystems with the top
three scores. For Management Effectiveness, the
top three scores were for the south-east Australian
Shelf, the Barents Sea and Prince Edward Islands,
and for Governance Quality it was West Coast
Vancouver Island, the south-east Australian Shelf
and the West Coast USA. In general, systems with
low average scores for Management Effectiveness
and Governance Quality questions combined had
low scores for the Management Effectiveness or
Governance Quality questions. This was not neces-
sarily the case for systems with high scores for
Management Effectiveness and Governance Qual-
ity. Most of the ecosystems had lower scores for
Governance Quality than Management Effective-
ness (22 ecosystems), 11 of which were lower by
more than 20%, and, in the case of the Irish Sea,
50%. On the other hand, the score for Governance
Quality for West Coast Vancouver Island was
much higher than Management Effectiveness
(which was also relatively high).
The rank order of the IndiSeas ecosystems from
this Survey was compared with the rank order
using the compliance with the Code of Conduct for
Responsible Fisheries scores from Pitcher et al.
0
1
2
3
4
5
6
7
Frq
stoc
k as
sess
men
ts?
Refe
renc
e po
ints
?
Dep
lete
d st
ocks
?
Freq
uent
rev
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?
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yste
m im
pact
s
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esse
d?
IUU
add
ress
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imiz
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nflic
t?
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-ter
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bjec
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?
Soci
al im
pact
s?
Econ
omic
impa
cts?
Har
vest
ing
sect
or
part
icip
atio
n?
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11
Scor
e
Figure 2 Responses averaged over the 27 ecosystems for each of Survey Questions with 95% confidence limits. White
bars refer to Management questions; grey bars refer to Governance questions.
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 13
Good fisheries management and governance A Bundy et al.
(2009a) for the 22 IndiSeas ecosystems for which
there were compliance scores available. The coun-
tries with the six top scores for each survey
(Fig. 4) were comparable, with two exceptions.
The eastern Scotian Shelf (Canada) had a lower
ranking in our Management Effectiveness and
Governance Quality Survey, and the Barents Sea
(Norway and Russia) had a higher one. However,
there were more differences in the rank order of
the rest of the ecosystems, in some cases substan-
tially, as illustrated in Fig. 4. For example, the
northern Humboldt (Peru) and Sahara Coastal
Morocco were ranked among the lowest three
using the scores from Pitcher et al. (2009a), but
were ranked in the middle of the range in this
analysis. Other ecosystems were given a lower
ranking by our Management Effectiveness and
Governance Quality Survey, such as the Catalan
Sea and the north-central Adriatic Sea.
Multivariate analysis
The first three principle components of the PCA
accounted for 53, 15 and 8% of the variation in
the data, a total of 76%. All survey questions had
high scores (positive (>0.3) or negative (<�0.3))
on at least one principle component (PC); thus, all
were useful in defining the clusters (Table 6). The
0
1
2
3
4
5
AU
ST
NW
US
BARE
N
NEU
S
WCV
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PORT
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EA
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TAN
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PORT
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ZA
BLA
CK
AD
RIA
MA
DA
G
GU
INE
CATA
L
ION
IA
(a)
(b)
(c)
Figure 3 Results of the Management Effectiveness and Governance Quality Survey ranked by (a) the score averaged
over all questions per ecosystem, (b) the average scores for Management Effectiveness and (c) the average scores for
Governance Quality. For acronyms, see Table 4.
14 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Cluster Analysis divided the 27 systems into two
large clusters and one unitary cluster (Fig. S1),
which were superimposed on the PCA (Fig. 5a).
Cluster 1 and West Coast Vancouver Island were
separated from Cluster 2 along PC1. As all survey
questions scored negatively on PC1, in general,
systems to the left of PC1 in Fig. 5 scored better
on all questions than those to the right side of the
figure. In particular, the defining questions for
PC1 (those with the highest negative scores) were
Q2 (Reference points), Q4 (Frequency of review),
Q6 (IUU (Illegal, Underreported and Unregulated)
fishing addressed) and Q11 (Harvesting sector par-
ticipation), Table 6.
PC2 was largely defined by Q9 and Q10 (Are
the social (economic) impacts of the fisheries man-
agement plan considered and formally evaluated
in management decisions?), with high positive
scores on PC2 (Table 6), providing a strong signal
that separated systems with some form of long-
term social and economic management objectives
(such as north-east USA and West Coast Vancou-
ver Island, systems at the top of Cluster 1), from
those without. The Irish Sea stands out from the
rest of Cluster 2, due to its low scores on Q8–Q11.PC3 is characterized by high positive scores on Q7
(Minimize conflict?) and Q11 (Harvesting sector
participation?) and high negative scores on Q5
(Ecosystem impacts addressed?) and Q1 (Frequency
stock assessments?). When PC2 was plotted
against PC3, the separation of the West Coast
Vancouver Island from the other ecosystems was
very clear (Fig. 5b), due to its high scores on PC2
(Q9 and Q10) and PC3 (Q7 and Q11), and its
lower scores on Questions 1 and 5 (PC3, Fig. 5b).
Although the questions were divided into Man-
agement Effectiveness and Governance Quality in
the survey, they did not completely group this
way in the PCA: Governance Qs 8, 9 and 10 all
scored positively on PC2, but Governance Q11
(Harvesting sector participation?) grouped with the
Management Effectiveness questions. In addition
to the survey questions that separate Cluster 1
and West Coast Vancouver Island from Cluster 2,
Figure 4 Heat Map showing the relative rankings of 22
IndiSeas ecosystems based on results from the
Management Effectiveness and Governance Quality
Survey. Also shown (left column) are the rankings from
the Pitcher et al. 2006 CCFR Survey. Shading from
highest rank (1 = red) to lowest rank (22 = blue). Note
that they are ranked based on the IndiSeas rankings. For
acronyms, see Table 4.
Table 6 Scores of variables on the first three principle
components of the PCA of 27 IndiSeas Ecosystems based
on the Management Effectiveness and Quality of
Governance Survey results. Bold numbers indicate higher
loadings on the principle components.
Survey Question PC1 PC2 PC3
1 Frequency of stockassessments?
�0.249 �0.19 �0.473
2 Reference points? �0.363 �0.098 �0.0033 Depleted stocks? �0.305 �0.251 0.1124 Frequency of review? �0.387 �0.05 0.0415 Ecosystem impacts
addressed?�0.228 �0.098 �0.674
6 IUU addressed? �0.347 �0.021 �0.0447 Minimize conflict? �0.315 �0.226 0.3788 Long-term objectives? �0.311 0.187 0.1079 Social impacts? �0.119 0.708 0.03310 Economic impacts? �0.257 0.54 �0.15311 Harvesting sector
participation?�0.338 �0.007 0.356
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 15
Good fisheries management and governance A Bundy et al.
it is notable that Cluster 1 is largely comprised of
systems from Europe, North America, and the
Pacific, whereas Cluster 2 is mainly comprised of
systems from the Mediterranean and Africa, sug-
gesting a geographic divide that may be related to
other social and economic factors, explored below.
Relationship to other ecosystem characteristics –BEST Analysis
Size was consistently selected as one of 2–3 exter-
nal ecosystem characteristics that best explained
the variability of the Survey data across all four
BEST analyses (Table 7) and political stability (a
proxy for the World Governance Indicators) was
selected in BEST 1, 2 and 3. In BEST analyses 2–4, where the ecological indicators were added, the
latter were always selected (SS in BEST 2, SS and
NDES in BEST 3, and SS, NDES and ES in BEST
4). All results were significant, and the highest
correlations between the ecosystem characteristics
and the survey data resemblance matrix were for
BEST 4, for ecosystem characteristics Size, HDI,
PC1
–4
–2
0
2
4
ADRIA
AEGEA
AUST
BALTI
BARENBISCA
BLCK
CADIZ
CATAL
CHANN
CHATH
ESS
GABES
GUINE
IONIA
IRISH
MADAG
NEUS
NHUMBNWUS
PE_IS
PORTU
SAHAR
SBENG
SENEG
TANZA
WCVI
12
3
45
6
7
8
9
10
11
High scores onmanagement and
governanceCluster 1 Cluster 2
Lower scores onmanagement
High scores onmanagement, lowerscore on governance
–6 –4 –2 0 2 4 6
–4 –2 0 2 4PC2
PC
3
–4
–2
0
2
4
ADRIA
AEGEA
AUST
BALTIBAREN
BISCA
BLCK
CADIZ
CATAL
CHANN
CHATH
ESS
GABES
GUINE
IONIA
IRISH
MADAG
NEUS
NHUMBNWUS
PE_IS
PORTU
SAHARSBENGSENEG
TANZA
WCVI
1
2
34
5
6
7
89
10
11
lower
High scores ongovernance Qs
9 and 10
Higher scores for frequency of stockassessment and ecosystem impacts but
scores for minimize conflict and harvestingsector participation
PC
2
(a)
(b)
Figure 5 PCA of 27 ecosystems using Management Effectiveness and Governance Quality results. (a) PC1 vs. PC2 and
(b) PC2 vs. PC3. Blue lines represent the scores of the survey questions on the principal components; length of line
reflects the importance of the loading, where a longer line indicates greater loading. For acronyms, see Table 4.
16 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
SS, NDES and ES. The results of Best 1a-3a con-
firm that the correlation results observed in BEST
4 were not the result of the smaller number of
ecosystems in this analysis (Table 7): that is, BEST
4 still resulted in the highest significant correlation
between the Survey data and the additional
ecosystem characteristics. Therefore, there was a
strong relationship between the ecological indica-
tors and the Survey data.
To visually compare the results of BEST 4 to the
results of the Survey, a PCA was run for the 11
ecosystems from BEST 4 using the five best ecosys-
tem characteristics (Fig. 6, Table 8). PC1
explained 54% of the variation in the data, and
was defined by SS, NDES and ES, that is, the eco-
logical status of the ecosystem. PC2 explained
26% of the variation in the data and was primar-
ily defined by size and HDI (Table 8). The results
are comparable to the PCA that used all 27 sys-
tems (Fig. 5). There were three main clusters
(although not significant (SIMPROF test)), but the
same ecosystems grouped together in each cluster.
These results indicate that the main pattern
observed in the Survey results can be reproduced
based largely on the ecosystem indicators, that is,
SS, NDES and ES, again illustrating the strong
relationship between management, governance
and ecosystem status. West Coast Vancouver
Island, north-east USA and the Barents Sea were
located to the left of all PCA plots, whether the
Survey data or the ecological and human dimen-
sions indicators were used; the southern Catalan
Sea, north-central Adriatic Sea and Guinea were
always located on the right-hand side of the PCAs
and the Irish Sea, northern Humboldt Current,
Portugal and southern Benguela Current were
located in the middle (Figs 5 and 6). Only the
eastern Scotian Shelf, which moved to the right of
the PC1, closer to the southern Catalan Sea, the
north-central Adriatic Sea and Guinean Shelf in
Fig. 6, changed position. Given the explanatory
power of PC1, it can be concluded that there is a
strong relationship between systems with high
Table 7 Results of the BEST analysis. For ecosystem characteristics abbreviations, refer to Table 3.
BEST AnalysisNumber ofSystems
Number ofecosystemcharacteristics Ecosystem characteristics q
Significance% level
BEST ecosystemcharacteristics
BEST 1 27 5 Size, HDI, Bad-SUBS,RandD, PS
0.459 0.1 Size; Political Stability
BEST 2 25 T6 Size, HDI, Bad-SUBS,RandD, PS, SS
0.507 0.1 Size; Political Stability; SS
BEST 3 18 7 Size, HDI, Bad-SUBS,RandD, PS, SS, NDES
0.562 0.1 Size; Political Stability;SS; NDES
BEST 4 11 8 Size, HDI, Bad-SUBS,RandD, PS, SS, NDES, ES
0.583 3.7 Size; HDI; SS; NDES; ES
BEST 1a 11 5 Size, HDI, Bad-SUBS,RandD, PS
0.407 13.3 Size; HDI
BEST 2a 11 6 Size, HDI, Bad-SUBS,RandD, PS, SS
0.558 3.7 Size; HDI, SS;
BEST 3a 11 7 Size, HDI, Bad-SUBS,RandD, PS, SS, NDES
0.570 3.4 Size; HDI, SS, NDES
–4 –2 0 2 4
PC1
–3
–2
–1
0
1
2
3
ADRIA
BAREN
CATAL
ESS
GUINE
IRISH
NEUS NHUMB
PORTU
SBENG
WCVI
Size
HDI
SS
NDES
INDISEAS 1
PC
2
Figure 6 PCA of 11 ecosystems using the five best
ecosystem characteristics from BEST4. Blue lines
represent the scores of the ecosystem characteristics on
PC1 and PC2; length of line reflects the importance of
the loading, where a longer line indicates greater
loading. For acronyms, see Table 4.
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 17
Good fisheries management and governance A Bundy et al.
(low) scores for Management Effectiveness and
Governance Quality and good (poor) ecosystem
and stock status. Size and HDI have less influence
on results, principally along PC2 and PC3. Gui-
nea’s low HDI, for example, separated it from the
other systems along PC2 (Fig. 6).
Discussion
Many nations are adopting or are considering the
adoption of EBFM; 67% of member States report-
ing to FAO’s Committee on Fisheries indicate that
they are implementing some form of an ecosystem
approach to fisheries (FAO 2014a,b), which
requires thinking, planning and acting at the
ecosystem scale. The analysis presented here repre-
sents the first real exploration of the relationship
between management, governance and ecosystem
status at the ecosystem scale. The main conclusion
was that higher scores for Management Effective-
ness and Quality of Governance were observed in
the ecosystems with better ecosystem and stock
status, suggesting that good ecosystem-based man-
agement and governance, and healthy ecosystems
go together. This is coherent with the results of
Coll et al. (2013) and Mora et al. (2009) studies
conducted at much broader scales, without local
experts involved in providing the information and
data, interpreting the analysis, and providing a
more hands-on understanding of management and
governance in these ecosystems. The benefit of the
finer scale analysis conducted here is that a more
nuanced understanding of how management and
governance contribute to ecosystem health was
achieved. Specifically, our results enabled the iden-
tification of aspects of the management and
governance that are important to ensure good
ecosystem status and also to specify, for different
systems, which aspects may need to be improved.
Responses to three questions related to Manage-
ment Effectiveness (Q2 (Reference points?), Q4
(Frequency of review?) and Q6 (IUU addressed?)
and Governance Quality Q11 (Harvesting sector
participation?), were key to distinguishing between
the 27 ecosystems. Responses to Governance Qual-
ity questions Q9 and Q10, regarding inclusion of
social and economic impacts in management
plans, led to further differentiation between these
systems. Q11, concerning harvesting sector partic-
ipation in fisheries management, was classed as a
governance question, but it aligned with the
responses to the Management Effectiveness ques-
tions in the PCA. Stakeholder participation in
resource management generally (Beierle 2002;
Reed 2008) and fisheries management specifically
(e.g. Jentoft and McCay 1995; Pomeroy et al.
2001; Beddington et al. 2007; Mora et al. 2009)
have been previously identified as important for
sustainable fisheries management and this is rein-
forced by our results. Our question about stake-
holder participation was quite simple; others have
noted the realities and complexities in engaging
stakeholders in fisheries research and decisions
making (e.g. Gray and Hatchard 2008; Pita et al.
2010; Mackinson et al. 2011).
Two questions, Q1 (Frequency of stock assess-
ments) and Q5 (Ecosystem impacts addressed), had
little influence on overall results, despite their
widely perceived importance in EBFM. Most
ecosystems scored well on Q1, but poorly on Q5,
suggesting positively that stock assessments were
generally being conducted frequently enough but
that ecosystem impacts were not yet being ade-
quately addressed. However, of the six ecosystems
with the highest rankings (averaged over the 11
questions), five had high scores (>3) for addressingecosystem impacts, underscoring that high per-
forming management systems tend to include con-
sideration of ecosystem impacts.
These overall results are consistent with analy-
ses conducted at the National or High Seas level
(Pitcher et al. 2006, 2009a,b; Mora et al. 2009;
Cullis-Suzuki and Pauly 2010; Coll et al. 2013);
however, our survey differed in several important
ways. We used a parsimonious set of 11 questions
that were empirically tried and tested prior to
finalizing the survey, questions were designed to
be objective, and documented evidence in support
Table 8 Results of the PCA of the 11 systems from
BEST 4: Percentage variation explained (top row) and
scores of variables on principal components in
subsequent rows. For ecosystem characteristics
abbreviations, refer to Table 6.
PC1 PC2 PC3
% variation 53.9 26.1 14.9Variable
Size �0.204 �0.574 0.78HDI �0.303 0.649 0.46SS �0.574 �0.16 �0.16NDES �0.520 0.345 �0.009ES �0.516 �0.323 �0.392
18 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
of the responses was required. Although the ques-
tions were adapted from Pitcher et al. (2006), our
intent was not to assess how well nations com-
plied with the Code of Conduct for Responsible
Fisheries, but to assess how well fisheries were
managed and governed, and to what extent
ecosystem considerations, including social and
economic aspects, were incorporated into long-
term management plans. Notably, few ecosystems
scored well on the latter questions, indicating an
opportunity for improvement within the manage-
ment and governance arena (Skern-Mauritzen
et al. 2016). This is consistent with Pitcher et al.
(2009a,b) who observed that countries scored
poorly on questions concerned with ecosystem-
based management. However, in contrast with the
Pitcher et al. (2009a) analysis, our results pro-
duced higher overall scores for control of illegal
fishing, suggesting that some progress may have
been made in this area. This is confirmed by a
recent FAO report on ‘Progress in the Implementa-
tion of the Code of Conduct for Responsible Fish-
eries and Related Instruments’ (FAO (2014a),
which indicates that following the recognition of
IUU fisheries as a problem in 90% of member
states, most have taken measures to combat this
threat.
The results of our ranking were generally coher-
ent with those of Pitcher et al. (2009a), with a
couple of exceptions; the Catalan Sea and the
north-central Adriatic Seas received notably lower
scores in this analysis, and the northern Humboldt
and Sahara Coastal Morocco received visibly
higher scores. We do not interpret this as a con-
tradictory result as the earlier large-scale analyses
do not necessarily reflect what is happening at the
smaller ecosystem scale (e.g. Marshall et al. 2015).
In the Pitcher et al. (2009a) analysis, the Catalan
Sea and the north-central Adriatic Seas were clas-
sified with the rest of Spain and Italy respectively,
whereas in this analysis, they were assessed at
much smaller scale. Both are highly exploited
ecosystems, so a lower ranking at this scale com-
pared to the country level makes sense. Notably,
the Catalan Sea and the north-central Adriatic
Seas, both Mediterranean systems, received similar
scores. It is well recognized now that, in general,
Mediterranean marine ecosystems lack manage-
ment and of those stocks with data, more than
90% are over-exploited (Colloca et al. 2013; Smith
and Garcia 2014; Vasilakopoulos et al. 2014). For
the northern Humboldt, Peru received a ‘fail’
grade of less than 40% for ‘compliance with the
code of conduct for use of reference points’ and
‘controlling illegal fishing’ in the Pitcher et al.
(2009a) analysis whereas the northern Humboldt
(representing Peru here) received scores >50% in
the Management Effectiveness and Quality of
Governance Survey for the comparable questions
Q2 and Q6. In January 2009, a new management
regime of individual vessel quotas was put in force
in the Peruvian anchoveta (Engraulis ringens,
Engraulidae) fishery. The overall effect of this new
system appears to have been positive in terms of
economic and ecological sustainability (Tveteras
et al. 2011). Interestingly, the phrasing of Q2 was
discussed at length during the development of the
Survey to ensure that it recognized different forms
of limit reference points. Morocco also received a
lower rank by Pitcher et al. (2009a), whereas
Sahara Coastal Morocco was ranked in the top 10
in this survey. Although Morocco is still at the
early stages of implementing EBFM (Kifani et al.
2008), in 2009 the Moroccan government
launched Plan HALIEUTIS, a strategy to enhance
long-term sustainability of its fisheries (http://
www.maroc.ma/fr/content/halieutis). There is
now consideration of the social and economic
dimensions of fisheries, even if they are not specifi-
cally incorporated in the long-term management
objectives. One example is the redirection of the
freezing industry from common octopus (Octopus
vulgaris, Octopodidae) to small pelagic fish after
the collapse of octopus in 2003.
As with all surveys, the potential subjectivity of
respondents cannot be ignored, and differences
between different survey results may be due to
subjectivity (Okoli and Pawlowski 2004). Here, we
tried to minimize this effect by selecting questions
based on fact, not opinion; we asked for documen-
tary evidence and encouraged the completion of
the survey by multiple experts. The level of coher-
ence with the results of Pitcher et al. (2009a) sug-
gests that this has been successful.
In general, the ecosystems surveyed received
better scores for the Management Effectiveness
questions than the questions about Governance
Quality, although there is a linear relationship
between their average scores (r2 = 0.55, not
shown). As the Management Effectiveness ques-
tions speak more to everyday fisheries manage-
ment, and the Governance Quality questions to
longer term strategic thinking and an explicitly
ecosystem approach to fisheries, this result is not
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 19
Good fisheries management and governance A Bundy et al.
too surprising as few systems have yet fully imple-
mented EBFM (Arkema et al. 2006; Long et al.
2015; Patrick and Link 2015). This is also high-
lighted by the poor scores across all ecosystems for
Q5 (Are ecosystem impacts addressed). A few sys-
tems, the West Coast Vancouver Island in particu-
lar, did have better results for Governance than
Management. This was due to lower scores for
Management Effectiveness questions Q1 (Fre-
quency of stock assessments), Q3 (Depleted stocks)
and Q5 (Ecosystem impacts addressed). There were
several reasons for these lower scores: (i) Fisheries
and Oceans Canada is moving towards providing
multiyear advice for some species (e.g. shrimp),
thereby reducing the frequency of stock assess-
ments (http://www.dfo-mpo.gc.ca/fm-gp/sdc-cps/
multi-year-pluriannuels-eng.htm, accessed 28
March 2016), although multiyear advice for
groundfish species preceded implementation of this
policy; (ii) groundfish, which accounted for more
than 85% of landings and comprised approxi-
mately 36 species, had a lower score for Q1,
which reduced the overall average and (iii) effec-
tive rebuilding (Q3) is difficult to judge for long-
lived species, such as rockfish (Sebastes spp.,
Sebastidae).
Overall, the ranking results and the results of
the multivariate analysis were consistent; the mul-
tivariate analysis separated four of the six top-
ranked ecosystems from the rest and clustered the
lowest ranking ecosystems together.
Relationship to other ecosystem characteristics
The results above, together with the higher overall
scores for Management Effectiveness, highlight the
difference between single-species management and
EBFM. Fisheries management bodies have been
practising single-species fisheries management for
decades, and although their success is debatable,
in some ecosystems good single-species fisheries
management can be effective, especially for
assessed species of high commercial value (e.g.
Dickey-Collas et al. 2010; Ricard et al. 2012;
Methot et al. 2013; Flood et al. 2016) and where
fisheries are the major pressure on the stock (as is
the case for many deep water offshore species,
such as orange roughy (Hoplostethus atlanticus) in
Australia). Developing and operationalizing EBFM
is a lengthy process, and even when practised,
management actions under EBFM take time to
adopt and implement, let alone to show effect
(Link 2010; Tallis et al. 2010; Skern-Mauritzen
et al. 2016).
However, our results support the thesis that
strong ecosystem-based management and gover-
nance, and healthy ecosystems go together: when-
ever an ecological indicator was included in the
BEST analysis, it was selected as one of two to
three factors that best described the survey data,
even when adjusted for sample size. Ideally, all 27
ecosystems, and all nine ecosystem characteristics,
would be included in this analysis, but these data
were not available for all systems. However, the
fact that one of the ecological indicators was
always an explanatory variable, even when 25
ecosystems were included, and had the highest
loadings on PC1, underscores the relationship
between effective fisheries management and gover-
nance and sustainable, healthy ecosystems.
Our results also indicated that broader physical,
social and economic factors such as size, political
stability and the human development index (HDI)
are related to fisheries management and gover-
nance, although that relationship is weaker than
for the ecological indicators. This relationship was
also apparent from the analysis of the Survey data,
which showed some geographic clustering of
ecosystems, although location was not an input:
south-east Australia, north-west USA, north-east
USA and West Coast Vancouver Island were all
located in the top left quadrant, indicating good
scores on both Management Effectiveness and
Governance Quality. The Mediterranean ecosys-
tems and most African ecosystems were all located
to the right of the PCA, with low scores for Man-
agement Effectiveness and Governance Quality.
These are systems with contrasting values for HDI
and political stability. This is typified by Guinea,
on the one hand, which has low HDI and was sep-
arated from the other 10 ecosystems in BEST 4,
and West Coast Vancouver Island, which has a
high HDI.
The relative influence of political stability and
HDI shifted in the results when the number of
ecosystems changed in the different BEST analyses,
for example compare BEST 2 and BEST 4
(Table 7). This is because there was greater con-
trast in the HDI values across the 11 ecosystems
than there was among the values for ‘Political Sta-
bility and Absence of Violence/Terrorism’ across
the 25 systems; therefore, it had more influence.
In effect, there is a fairly strong relationship
between ‘Political Stability and Absence of
20 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Violence/Terrorism’ and HDI, with a correlation
coefficient of 0.75. Most of the additional social
and economic factors that were explored for the
BEST analysis were highly correlated for the coun-
tries included in this analysis, which does raise
questions concerning how these data are used for
other purposes. For example, using multiple indi-
cators with the same trend can lead to an overem-
phasis on the property that they represent.
Ecosystem size was consistently selected as an
explanatory variable in the BEST analysis: the
seven ecosystems with greater than average size
(>230 000 km2) were among the nine ecosystems
with the highest scores on PC1, suggesting that
fisheries in larger ecosystems are better managed
and that these ecosystems have better ecological
status. Further, for the 27 ecosystems, there was a
strong linear relationship between Survey score
and size (r2 = 0.54, P < 0.001, Fig. S2). The two
exceptions to the trend were the West Coast Van-
couver Island and Chatham Rise ecosystems,
which were below the average ecosystem size
(<230 km2), but had high PC1 scores. In the case
of the Chatham Rise, a high proportion of the
landed biomass is from migratory species (e.g.
Macruronus novaezelandiae, Merlucciidae), which
are managed over larger spatial scales than Cha-
tham Rise ecosystem. The West Coast Vancouver
Island includes transboundary stocks, such as
Pacific salmon (Oncorhynchus spp., Salmonidae)
and Pacific hake (Merluccius productus, Merlucci-
idae). In both cases, management decisions for
these species relate to these larger areas.
The general result that larger ecosystems are
better managed may be related to the portfolio
effect (Schindler et al. 2015). This is where for
large ecosystems there is the possibility to switch
target species or relocate effort. Smaller ecosystems
may have less capacity to easily redirect pressure
to other locations to give species, or habitats, a
release from fishing pressure and time to recover.
However, managing fisheries at the large scale of
south-east Australia or Barents Sea ecosystems is
an expensive undertaking, requiring good institu-
tional structure and lengthy time investment. This
underscores that successful EBFM takes time.
Although the ecosystems included in this study
had a wide size range, all, with the exception of
south-east Australia, were smaller than the LME
scale and most were smaller than EEZ. However,
as larger ecosystems did achieve higher rankings
for management effectiveness and governance
quality, this does raise the question of whether lar-
ger ecosystems would always result in a higher
ranking, or whether there is an upper limit to this
relationship. Factors such as complexity of the
fisheries and the number of national jurisdictions
generally increase with ecosystem size and would
be likely to compromise fisheries management
effectiveness and governance quality. The results
of this analysis indicate that complexity of fisheries
does affect Management Effectiveness and Gover-
nance Quality: the ecosystems that were more
multispecies, multisector and, therefore, more
complex (e.g. Mediterranean and Guinean ecosys-
tems) had the lowest survey scores. In contrast,
the Barents Sea, which had high scores, is a high
latitude ecosystem with a relatively simple species
composition and fisheries sector, which may make
it easier to map, monitor and manage. On the
other hand, survey scores for the five multijuris-
dictional ecosystems that were included in this
assessment (the central Baltic Sea, the Barents
Sea, the eastern English Channel, the Irish Sea
and the north-central Adriatic) ranged from high
to low. Interestingly, with the exception of the
north-central Adriatic, all multijurisdictional
ecosystems scored poorly on the Governance Ques-
tions, especially related to whether social or eco-
nomic impacts of the fisheries management plan
were considered and formally evaluated in man-
agement decisions. Therefore, incorporating social
and economic consideration may be more difficult
to enact in multijurisdictional ecosystems. To
explore the question of the relationship of ecosys-
tem size with complexity of the fisheries and the
number of national jurisdictions would require a
large number of ecosystems with ecological indica-
tors representing all possible combinations of size,
HDI and fisheries complexity and number of juris-
dictions.
A more nuanced view of the results
We have used simple indicators for this compara-
tive study, which have proven useful for ranking
and assessment purposes. This approach necessar-
ily aggregates a lot of information, and it misses
some of the nuances and detail of individual sys-
tems. It would be a mistake to assume that these
results tell the whole story and that all is well
with the high-ranking ecosystems, and all is
wrong with the low-ranking ecosystems. The
southern Benguela, for example, was ranked in
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 21
Good fisheries management and governance A Bundy et al.
the top third of ecosystems in this and other
assessments cited here, which may be considered
‘good enough’ for a developing society. A closer
look, however, reveals that some of its important
fisheries are problematic with respect to gover-
nance issues, such as stakeholder representation
(Hara et al. 2014; Norton 2014), transparent and
defensible rights allocation process, for example, in
small-scale fisheries (see, e.g. Norton 2014 and
Gammage 2015 for overviews) and mistrust
among stakeholders (Hara et al. 2014; Duggan
et al. 2014; Ragaller 2012). Further, economic
objectives override social objectives in the large
fisheries (e.g. Cooper et al. 2014) without explicit
consideration of trade-offs, and spatial manage-
ment is slow to be implemented in the small pelag-
ics fishery (Howard et al. 2007; Coetzee et al.
2008). Overlaid with expected changes due to cli-
mate change (e.g. Jarre et al. 2015) and political
instability (Nel et al. 2007; Petersen et al. 2010;
Norton 2014), these weaknesses may well com-
promise the ability of the southern Benguela to
provide important ecosystem services into the
future.
Here, we explore some of the details that under-
lie the results of the Management Effectiveness
and Governance Quality Survey and, in doing so,
underscore the need for the involvement of local
experts in the interpretation of the result of global
assessments. The existence of long-term manage-
ment plans and consideration of ecosystem
impacts is typical of ecosystems with the highest
scores for both Management Effectiveness and
Governance Quality. However, even with effective
management, governance quality varied. For
example, the West Coast Vancouver Island had
high Governance Quality scores whereas the Bar-
ents Sea had lower scores. This difference was lar-
gely due to the degree to which social and
economic impacts were included in long-term
management plans (Qs 9 and 10). The West Coast
of Vancouver Island fisheries are managed by Fish-
eries and Oceans Canada (DFO), and Canada’s
National Acts, regulations, and policies require
that DFO consults with industry, non-government
organizations, and First Nations through consulta-
tive boards or committees. In the Barents Sea, fish-
eries management has formally existed since the
1930s (Grønnevet 2015). Since 2005, all Norwe-
gian EEZ ocean areas have established manage-
ment plans that include economic and social
information, but there is not a focus on their
impacts. Therefore, there is still a room for
improvement of the governance of the Barents
Sea, as shown in this study, and previously sug-
gested by the European Union project ‘Monitoring
and Evaluation of Spatially Managed Areas’ (Stel-
zenm€uller et al. 2013).
Two major eastern boundary current upwelling
systems, southern Benguela and northern Hum-
boldt, were ranked 9th and 10th, respectively, in
this Survey; they had similar values for size, HDI,
SS and ES, although NDES was higher (better) in
the southern Benguela, and they were located
adjacent to one another in the PCA analyses. The
similarity of their results is perhaps not surprising
as they share many characteristics such as rela-
tively low species diversity and fisheries for small
pelagics (historically anchovies (Engraulidae) and
sardines (Clupeidae)) and hakes (Merluccius spp.
Merlucciidae) that dominate other fisheries by vol-
ume and value, and which have international
markets. Despite the developing status of their
societies and hence limited government support
for marine science, the management of these large
fisheries has for decades attracted government sup-
port and the attention of the international fisheries
science community. These large fisheries, in con-
trast to many smaller fisheries in these countries,
are therefore better managed than may be appar-
ent from their HDI values. However, one key dif-
ference between them is the higher economic
contribution of anchovy to society in northern
Humboldt (FAO, 2010). This may explain why the
northern Humboldt achieved higher scores for
minimizing conflict in fisheries, and hence Gover-
nance Quality, due to the importance its fisheries.
The Portuguese EEZ, another upwelling system,
ranked 13th in this survey, had similar scores to
the two upwelling systems, the eastern Scotian
Shelf, Bay of Biscay, and the eastern English Chan-
nel. This mostly reflects implementation of the
European Common Fisheries Policy with long-term
management plans, reference points and targets
(EU 2008, 2015), as well as the Marine Frame-
work Strategy Directive (MSFD, 2008/56/EC),
which requires consideration of the ecosystem
impacts of fishing. In Portugal, stakeholders are
increasingly included in developing management
plan objectives as in the case of the Portuguese-
Iberian sardine fishery, which has a management
plan with a strong national stakeholder participa-
tion and social impacts considered (DGRM 2012).
22 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.
Although also part of the European Union and
therefore subject to the European Common Fish-
eries Policy, the Irish Sea was somewhat separated
from the other ecosystems in the Survey PCA. This
was caused by its low scores on the Governance
Quality questions, largely due to the lack of long-
term, multispecies management plans. Fisheries
management to date has been almost entirely sin-
gle-species based and also tended to focus on
immediate problems such as the need to rebuild
the Irish Sea cod stock (Kelly et al. 2006). ICES is
beginning to develop ecosystem-based assessments
for Irish Sea stocks and will eventually develop an
overall EBFM plan, but this work has only recently
commenced (ICES 2016c). This ecosystem is also
transboundary and comes under multiple jurisdic-
tions (England, Northern Ireland, Ireland, Wales
and the Isle of Man), and this may be one reason
why its governance has been relatively weak
despite it being located in a high HDI area with
the political systems being reasonably well aligned.
The African and Mediterranean Sea ecosystems
grouped together in both PCAs, due to their poor
scores on most Survey questions, and their rela-
tively poor ecological status. Guinea, for example,
has a low HDI, no fisheries policy and other regu-
latory mechanisms are inadequate, which has led
to the development of IUU fishing (MRAG-DFID
2005; Boto et al. 2009). Furthermore, scientific
assessments, which were frequent and rigorous
from 1985 to 1995, in collaboration with IRD
(Institut de Recherche pour le D�eveloppement)
have since become very irregular (Domain et al.
1999). The translation of scientific advice into sus-
tainable fisheries management policy is limited
(Fontana 2015). Recent studies on the state of the
Guinean continental shelf show that this ecosys-
tem is degraded (Camara et al. 2016). Abundance
indices are down, and trade sizes have decreased.
These factors threaten the sustainability of Gui-
nean fishing (Domain et al. 1999). Similarly, Sene-
gal has a low HDI with a relatively small size and
poor ecological status. Despite the economic and
social importance of the fisheries sector in Senegal,
it has faced considerable challenges for several
years, mainly due to the lack of effective manage-
ment and governance approach (Thiao and Lalo€e
2012). Historically, the public policies to improve
the management and governance of the fisheries
sector and to rebuild major fish stocks are ineffec-
tive because of many socioeconomic and manage-
rial constraints that undermine any attempt to
reduce the fishing pressure, restore and conserve
the coastal ecosystem and regulate economic
incentives (Thiao and Lalo€e 2012).
Low HDI, however, does not explain the poor
results for the north-central Adriatic or the south-
ern Catalan Sea, both of which are part of the EU,
with HDI values comparable to those for the rest of
Europe (http://hdr.undp.org/en, accessed February
2016). In the Mediterranean, fisheries have a rela-
tively low economic importance, with relatively low
catches (Eurostat 2013). They are also multispecies,
multigear, and operated by an extremely large
number of mostly small-scale fishing vessels along
an extended coastline, with a large number of land-
ing points. In such systems, the direct and indirect
interactions among multigear fisheries should be
taken into account when implementing fisheries
plans (Moutopoulos et al. 2013) to reinforce the
positive trade-offs (Link 2010). All these qualities
may render their management (and surveillance)
quite costly and difficult to control (Colloca et al.
2013). Therefore, the poor scores for Management
Effectiveness and Governance Quality, and the poor
ecological status of the north-central Adriatic or the
southern Catalan Sea may be due to the low priority
given to fisheries, their complexity, and the lack of
investment in them. It is noteworthy that even
though fishing activities in the Mediterranean
extend back centuries, (i) fishery science is under-
funded and has developed more recently, (ii) inter-
national collaborations and governance through
the RFMO (General Fisheries Commission for the
Mediterranean) is weak and there is a large propor-
tion of IUU (Pauly et al. 2014), while (iii) priority
has been given by the EU to its Atlantic fisheries
(Smith and Garcia 2014). Note that the five
Mediterranean systems are grouped together in the
PCA, indicating that these issues are resulting in
poor Management Effectiveness and Governance
Quality throughout the Mediterranean, and possible
poor ecological status, as shown with ecological
indicators (Coll et al. 2016).
Finally, the PCA results for the eastern Scotian
Shelf using the Survey data and the ecological
indicators were different. The latter associated the
eastern Scotian Shelf with ecosystems that had
lower scores for ecosystem status. This is because
the ecological status of the eastern Scotian Shelf is
a reflection of past management and governance
and not the current practice. In the early 1990s,
the cod (Gadus morhua, Gadidae) fishery collapsed,
other groundfish fisheries were reduced to low
©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F I SHER IES 23
Good fisheries management and governance A Bundy et al.
levels and a groundfish moratorium was intro-
duced (Bundy et al. 2009). The moratorium con-
tinues to the present day, but cod and many other
groundfish are still at low biomass levels. The low
values for SS, NDES, and ES largely reflect these
changes in the fish community. However, there
have been several changes to management and
governance as reflected by DFO’s adoption of the
precautionary principle and the Sustainable Fish-
eries Framework (http://www.dfo-mpo.gc.ca/fm-
gp/peches-fisheries/fish-ren-peche/sff-cpd/overview-
cadre-eng.htm, accessed 23 Dec 2015). Now,
invertebrate species such as lobster, snow crab
and shrimp form the basis of well-managed fish-
eries on the eastern Scotian Shelf.
Conclusions
Despite misunderstandings and myths (Patrick and
Link 2015), and an array of definitions and princi-
ples (Arkema et al. 2006; Long et al. 2015), EBFM
is beginning to happen (FAO 2014a). We conclude
that systems with higher scores for Management
Effectiveness and Quality of Governance have
higher scores for ecosystem and stock status. This
supports the assertion that strong and effective
ecosystem-based fisheries management combined
with a strategic vision are likely to promote good
ecosystem status. Key factors that point to success
in this analysis are the use of reference points, rea-
sonably frequent review of assessments, addressing
IUU and importantly, inclusion of stakeholders to
ensure adequate debate of issues and exploration
of possible solutions in decision-making process.
At the same time, there should be long-term man-
agement plans, which need to include the eco-
nomic and social dimensions of exploited
ecosystems and also take into account the multi-
species and wider ecosystem interactions of fish-
eries (Skern-Mauritzen et al. 2016). By definition,
it is very difficult to implement EBFM in ecosys-
tems where there is no EBFM plan. Increasingly,
EBFM also needs to be implemented as one compo-
nent of a wider process of marine planning in
order to ensure that developments across all sec-
tors do not lead to further environmental degrada-
tion (Long et al. 2015).
Acknowledgements
We gratefully acknowledge the many individual
experts who took the time to complete the
Management Effectiveness and Governance Quality
Survey: Dan L. Ayres, Fatima Borges, Briana
Brady, Ra�ul Castillo, Jaclyn Cleary, Andrew Cock-
croft, Murat Dagtekin, Erich Diaz, Johan de Goede,
Moustapha Deme, Deon Durholtz, Linnea Flos-
trand, Didier Gascuel, Juan Gil, Leigh Gurney,
Razafindrainibe Hajanirina, James Hastie, Tarek
Hattab, Rosemary Hurst, Jim Irvine, Othman Jar-
boui, Isaac Kaplan, Erkan Kideys, Rob Kronlund,
Frida Ben Rais Lasram, Robert Leslie, C.J.P. Manel,
Kristin Marshall, Patroba P. Matikum, Alberto
Murta (deceased), Corey Niles, Isabel Palomera,
Jo~ao Pereira, Ian Perry, Fernando Ramos,
Mohamed Salah Romdhane, Ingolf Røttingen,
Francesc Sarda, Jake Schweigert, Alexandra Silva,
Luis Silva, Brenda Spence, Youen Vermard,
Yolanda Vila, Henning Winker, Tana Worcester
and Greg Workman. The authors also thank Herv�e
Demarcq, IRD, France, for preparation of Fig. 1.
This is a contribution to the IndiSeas Working
Group, which, by the time of the study, was co-
funded by IOC-UNESCO (www.ioc-unesco.org),
EuroMarine (http://www.euromarinenetwork.eu),
the European FP7 MEECE research project, the
European Network of Excellence Eur-Oceans and
the FRB EMIBIOS project (contract n°212085).The authors wish to thank their funding organiza-
tions, too numerous to mention here, for enabling
them to participate in the IndiSeas programme
and to make time available to contribute to this
study.
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Supporting Information
Additional Supporting Information may be found
in the online version of this article:
Table S1 Management Effectiveness and Gover-
nance Quality Survey Template, including instruc-
tions to experts and a glossary of terms.
Table S2 Weighting factors for estimation of
average ecosystem compliance scores for multi-jur-
isdictional ecosystems.
Table S3 Additional social, economic, governing
and ecological indicators used in BEST analysis.
Table S4 Spearman correlations between social
and economic indicators for the 27 IndiSeas ecosys-
tems. Acronyms are provided in Table S3. Indica-
tors in bold were used in the BEST Analysis1.
Table S5 Average Scores for each of the 11
questions from the Management Effectiveness and
Governance Quality Survey.
Figure S1 Cluster analysis of the 11 Manage-
ment Effectiveness and Governance Quality Survey
results.
Figure S2 Standardised average Management
Effectiveness and Governance Quality Survey
scores plotted against ecosystem size (squareroot
transformed and standardised).
28 ©2016 Her Majesty the Queen in Right of Canada. Fish and Fisheries published by John Wiley & Sons Ltd., F I SH and F ISHER IES
Good fisheries management and governance A Bundy et al.